Images having low or high resolution are typically captured by use of a camera, Charge Coupled Device (CCD), IR camera, or Flat Panel Detector (FPD) with a visible, Infrared, or X-ray light source, respectively. In many cases, such as in medical radiography applications, it might not be possible to capture the whole object of interest in a single field of view or a single image. Therefore, multiple views of an area of interest are typically acquired as multiple images by automatically (synchronously) or manually (asynchronously) moving the sensor and light source with respect to the object of interest. Physical movement of the sensor and light source can be accomplished by horizontal movement only, vertical movement only, both horizontal and vertical movement, or rotational movement.
In Digital Radiographic (DR) applications, both the X-ray light source and FPD are typically moved vertically or horizontally in order to acquire multiple images (e.g. of a patient's spine or leg for scoliosis or long bone study for bone alignment, or for other physiological measurements). Clinicians, however, generally prefer a single image showing “a whole region of interest” for medical study and diagnosis. Yet, because of the large size of some objects of interest, e.g. long bones, or a very high resolution requirement for a small object, multiple image acquisition is the only viable option. Stitching algorithms exist that can combine multiple images (e.g. sequences of images) into a single overall image of the region of interest.
What is needed is a stitching method that can more accurately and more efficiently fuse (combine) multiple sequences of images to create a single image of interest from multiple acquired images.